What is CJ Path?
CJ Path is an open source application for Customer Journey Analysis. Customer journey paths are visual representations of the various touchpoints toward a conversion. They show how and when each customer interacts with multiple marketing channels such as advertising, social and website before they make a purchase, or does not make a purchase.
CJ Path helps marketers to understand exactly how well each marketing method is performing and how each method interacts with each other. This leads to a better understanding of the customer and maximizing marketing performance.
CJ Path is completely interactive, you can re-define business goals for touchpoints and conversions and redraw the journey path immediately.
Why use CJ Path?
Customer journey analysis is rapidly emerging in the market as a way of better understanding the broad range of interactions between a company and the audience of potential and existing customers. Because it requires very complex processing on massive amounts of data, it is typically a very expensive and time consuming undertaking. Although there are a wide variety of commercial solutions, both software and service based, there has been no simple free tool to perform this type of analysis, until now.
CJ Path is the first completely free solution for customer journey analysis. It can be used to do the following:
- Data fusion
- Identity resolution
- Interactive journey path visualization
- Behavior based customer segmentation
- Clustering and look-alike behavioral analysis
As an open source software, it is completely customizable and can be integrated with most data sources, BI and visualization tools.
What kind of data does CJ Path accept?
CJ Path uses time stamped data as the source for creating a cohesive customer journey for each uniquely identified customer.
Raw data files like logs are ideal compared to more aggregated data. Examples of data sources can include web logs, call center logs, purchase logs, marketing logs, etc.
In addition, other data can be used to enrich and add context to the data such as demographic, financial, weather, sales, etc.